Conference paper Open Access
Mete, Muhammed Oguzhan; Yomralioglu, Tahsin
Property value is needed in many transactions such as purchase and sale, taxation, expropriation, capital market activities. Geographic Information Systems (GIS) and Machine Learning methods are widely used in automated mass appraisal practices. Analysing the Machine Learning based mass appraisal applications, it is seen that locational criteria are insufficiently used during the price prediction process. Whereas, locational criteria like proximity to important places, sea or green areas views, smooth topography are some of the spatial factors that extremely affect the property value. In this study, a hybrid approach is developed by integrating GIS and Machine Learning for mass appraisal of residential properties in England and Wales.
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